Position Summary
- As an active team member of the Computational Innovation department at the Client, the successful candidate will contribute to oncology drug discovery research through in silico data driven approaches.
- You will leverage multi-modal omics data analysis and collaborate with biologists to solve scientific challenges to advance drug discovery programs.
- This opportunity can be remote.
Duties and Responsibilities:
- Support Oncology drug development efforts.
- Identify, learn and apply emerging technologies in data science and its applications to novel cancer therapeutics discovery and development.
- Apply and develop innovative analysis approaches when standard methods are not adequate.
- Identify and process publicly available and internally generated datasets using statistical and bioinformatics techniques to create meaningful biological insights.
- Follow relevant scientific literature to ensure use of optimal methods and understand emerging practices across the field.
- Interpret, report, and present analysis results, with a high level of integrity and ethics, to biologists and collaborators.
- Ensure FAIR data analysis with clear documentation and reproducibility.
Skills:
- Programming experience with Python and R for bioinformatic data analysis in unix-like systems.
- Proficiency in working with bulk and single cell NGS data.
- Experience with any of these topics is a plus: oncology or immunology knowledge, spatial transcriptomics, methylation, or liquid biopsy data analysis, public oncology database datasets (TCGA, GTEX, Human cell atlas, CZ CELLxGene Discover, Human tumor atlas network, etc).
- Proficiency in working with high performance computing clusters (HPC).
- Proficiency in biological pathway analysis.
Qualifications:
Education: PhD degree from an accredited institution with experience in Computational Sciences or a related Scientific discipline (e.g., Computer sciences, Computational Biology, Genomics, Biostatistics, Bioinformatics and Biological Sciences).